Energy-Efficient Concurrency Control for Dynamic-Priority Real-Time Tasks with Abortable Critical Sections

In this paper, we are interested in energy-efficient concurrency control for real-time tasks on a non-ideal DVS processor. Based on well-known ceiling-based concurrency control protocols (such as priority ceiling protocol (PCP) and stack resource policy (SRP)), researchers have proposed energy-efficient approaches to mange concurrent accesses to shared resources so that the energy consumption can be reduced. However, ceiling-based protocols have a problem of ceiling blocking which imposes a great impact on the performance of real-time systems. In order to achieve sufficient performance, we propose a new protocol, called conditional abortable stack resource policy (CA-SRP), to resolve the ceiling blocking problem for dynamic-priority real-time tasks by incorporating a conditional abort rule into SRP. Based on the schedulability analysis of CA-SRP, we also propose a method, called dynamic speed assignment (DSA), to dynamically calculate and assign proper processor speeds for task execution so that the energy consumption can be reduced further. The capabilities of our proposed CA-SRP and DSA have been evaluated by a series of experiments, for which we have encouraging results

Heuristic Approach for Scheduling Dependent Real-Time Tasks

Reducing energy consumption is a critical issue in the design of battery-powered real time systems to prolong battery life. With dynamic voltage scaling (DVS) processors, energy consumption can be reduced efficiently by making appropriate decisions on the processor speed/voltage during the scheduling of real time tasks. Scheduling decision is usually based on parameters which are assumed to be crisp. However, in many circumstances the values of these parameters are vague. The vagueness of parameters suggests that to develop a fuzzy logic approach to reduce energy consumption by determining the appropriate supply-voltage/speed of the processor provided that timing constraints are guaranteed. Intensive simulated experiments and qualitative comparisons with the most related literature have been conducted in the context of dependent real-time tasks. Experimental results have shown that the proposed fuzzy scheduler saves more energy and creates feasible schedules for real time tasks. It also considers tasks priorities which cause higher system utilization and lower deadline miss time

Heuristic Approach for Scheduling Dependent Real-Time Tasks

Reducing energy consumption is a critical issue in the design of battery-powered real time systems to prolong battery life. With dynamic voltage scaling (DVS) processors, energy consumption can be reduced efficiently by making appropriate decisions on the processor speed/voltage during the scheduling of real time tasks. Scheduling decision is usually based on parameters which are assumed to be crisp. However, in many circumstances the values of these parameters are vague. The vagueness of parameters suggests that to develop a fuzzy logic approach to reduce energy consumption by determining the appropriate supply-voltage/speed of the processor provided that timing constraints are guaranteed. Intensive simulated experiments and qualitative comparisons with the most related literature have been conducted in the context of dependent real-time tasks. Experimental results have shown that the proposed fuzzy scheduler saves more energy and creates feasible schedules for real time tasks. It also considers tasks priorities which cause higher system utilization and lower deadline miss time

Processor Speed Control for Power Reduction of Real-Time Systems

Reducing energy consumption is a critical issue in the design of battery-powered real time systems to prolong battery life. With dynamic voltage scaling (DVS) processors, energy consumption can be reduced efficiently by making appropriate decisions on the processor speed/voltage during the scheduling of real time tasks. Scheduling decision is usually based on parameters which are assumed to be crisp. However, in many circumstances the values of these parameters are vague. The vagueness of parameters suggests that to develop a fuzzy logic approach to reduce energy consumption by determining the appropriate supply-voltage/speed of the processor provided that timing constraints are guaranteed. Intensive simulated experiments and qualitative comparisons with the most related literature have been conducted in the context of dependent real-time tasks. Experimental results have shown that the proposed fuzzy scheduler saves more energy and creates feasible schedules for real time tasks. It also considers tasks priorities which cause higher system utilization and lower deadline miss time

MORA: an Energy-Aware Slack Reclamation Scheme for Scheduling Sporadic Real-Time Tasks upon Multiprocessor Platforms

In this paper, we address the global and preemptive energy-aware scheduling problem of sporadic constrained-deadline tasks on DVFS-identical multiprocessor platforms. We propose an online slack reclamation scheme which profits from the discrepancy between the worst- and actual-case execution time of the tasks by slowing down the speed of the processors in order to save energy. Our algorithm called MORA takes into account the application-specific consumption profile of the tasks. We demonstrate that MORA does not jeopardize the system schedulability and we show by performing simulations that it can save up to 32% of energy (in average) compared to execution without using any energy-aware algorithm.Comment: 11 page

Power-Aware Real-Time Scheduling on Identical Multiprocessor Platforms

In the following, we consider the problem of minimizing the energy consumption needed for executing a set of real-time tasks scheduled on a fixed number of identical processors. The scheduling is preemptive and follows the global EDF policy. ``Global'' scheduling algorithms, on the contrary to partitioned algorithms, allows different instances of the same task (also called jobs or processes) to be executed upon different processors. Each process can start its execution on any processor and may migrate at run-time from one processor to another if it gets preempted by smaller-deadline processes. We first tackle the problem of choosing the smallest admissible processor frequency for the set of CPUs such that all deadlines will be met considering the worst-case workload. The procedure is performed off-line and provides a static result in the sense that the computed speed does not change over time. Such a static solution is necessary, however, due to the discrepancy between worst-Case Execution Times (WCET) and Actual-Case Execution Times (ACET), it usually leads to very conservative results. In a second step, we thus propose an on-line ``slack reclaiming'' scheme that monitors task executions and take advantage of unused CPU time to further reduce frequency

Dynamic Voltage Scaling for Energy- Constrained Real-Time Systems

The problem of reducing energy consumption is dominating the design of several real-time systems. The Dynamic Voltage Scaling (DVS) technique, provided by most microprocessors, allow to balance computational speed versus energy consumption. We present some novel energy-aware scheduling algorithms that allow to expoit this technique while meeting real-time constraints. In particular, we present the GRUB-PA algorithm which, unlike most existing algorithms, allows to reduce energy consumption on real-time systems consisting of any kind of task. We also present a working implementation of the algorithm on Linux